Artificial Intelligence for Energy Efficiency is a comprehensive exploration of AI application technologies. The book integrates AI algorithms with the operational principles of electrical machinery and energy systems and introduces how these algorithms can alter the operational characteristics of such systems. With a focus on their use in enhancing energy efficiency, it imparts interdisciplinary knowledge and a deep understanding of the principles and methods of AI applications. The book begins with an overview of global trends in enhancing energy efficiency, followed by an introduction to AI algorithms applied in this field. Subsequent chapters, supported by industry case studies, delve into AI applications in enhancing motor efficiency, building and energy saving for building equipment, and smart city development. The book also addresses AI computing power saving and discusses the evolution of AI and the limits of energy efficiency improvement. It concludes with future prospects and the most beneficial application of AI for sustainable human development. Artificial Intelligence for Energy Efficiency is an essential read for graduate students in mechanical, electrical, architectural, and energy-related fields, as well as researchers interested in the intersection of AI and energy efficiency. This comprehensive guide offers a wealth of research case studies, making it a valuable reference tool for professionals in the energy sector.
1. Chapter 2. Introduction to AI algorithms applied in enhancing energy efficiency - p. 15 2. 2.1 Sixty effective AI algorithms into five categories - p. 16 3. 2.1.1 Evolutionary algorithm (EA) - p. 21 4. 2.1.2 Expert system (ES) - p. 61 5. 2.1.3 Discriminative AI (DAI) - p. 66 6. 2.1.4 Predictive AI (PAI) - p. 91 7. 2.1.5 Generative AI (GAI) - p. 129 8. 2.2 AI-assisted energy management - p. 140 9. 2.3 AI-enabled advanced control - p. 146 10. 2.4 AI-assisted fault detection and diagnosis (AI-assisted-FDD) - p. 154 11. 2.5 Energy saving effect and energy efficiency improvement - p. 161 12. Chapter 3. AI applications in enhancing motor efficiency - p. 175 13. Chapter 4. AI applications in buildings and energy saving for building equipment - p. 213 14. Chapter 5. AI applications for smart city development and urban sustainability - p. 303 15. Chapter 6. AI computing power saving - p. 349 16. Chapter 7. The evolution of AI and the limits of energy efficiency improvement - p. 375 17. Chapter 8. Conclusions and future prospects on applying AI for energy efficiency - p. 403 18. Index - p. 413
Artificial Intelligence for Energy Efficiency is a comprehensive exploration of AI application technologies. The book integrates AI algorithms with the operational principles of electrical machinery and energy systems and introduces how these algorithms can alter the operational characteristics of such systems. With a focus on their use in enhancing energy efficiency, it imparts interdisciplinary knowledge and a deep understanding of the principles and methods of AI applications. The book begins with an overview of global trends in enhancing energy efficiency, followed by an introduction to AI algorithms applied in this field. Subsequent chapters, supported by industry case studies, delve into AI applications in enhancing motor efficiency, building and energy saving for building equipment, and smart city development. The book also addresses AI computing power saving and discusses the evolution of AI and the limits of energy efficiency improvement. It concludes with future prospects and the most beneficial application of AI for sustainable human development. Artificial Intelligence for Energy Efficiency is an essential read for graduate students in mechanical, electrical, architectural, and energy-related fields, as well as researchers interested in the intersection of AI and energy efficiency. This comprehensive guide offers a wealth of research case studies, making it a valuable reference tool for professionals in the energy sector.
1. Chapter 2. Introduction to AI algorithms applied in enhancing energy efficiency - p. 15 2. 2.1 Sixty effective AI algorithms into five categories - p. 16 3. 2.1.1 Evolutionary algorithm (EA) - p. 21 4. 2.1.2 Expert system (ES) - p. 61 5. 2.1.3 Discriminative AI (DAI) - p. 66 6. 2.1.4 Predictive AI (PAI) - p. 91 7. 2.1.5 Generative AI (GAI) - p. 129 8. 2.2 AI-assisted energy management - p. 140 9. 2.3 AI-enabled advanced control - p. 146 10. 2.4 AI-assisted fault detection and diagnosis (AI-assisted-FDD) - p. 154 11. 2.5 Energy saving effect and energy efficiency improvement - p. 161 12. Chapter 3. AI applications in enhancing motor efficiency - p. 175 13. Chapter 4. AI applications in buildings and energy saving for building equipment - p. 213 14. Chapter 5. AI applications for smart city development and urban sustainability - p. 303 15. Chapter 6. AI computing power saving - p. 349 16. Chapter 7. The evolution of AI and the limits of energy efficiency improvement - p. 375 17. Chapter 8. Conclusions and future prospects on applying AI for energy efficiency - p. 403 18. Index - p. 413
